class_docstr: Character-level CNN encoder to generate word representations, as input to
  transformer encoder.
code: def prepare_for_onnx_export_(self):
      self.onnx_export_model = True
  
imports: import logging
  import math
  from ast import literal_eval
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq.models import FairseqEncoder, register_model, register_model_architecture, transformer
  from fairseq.modules import SinusoidalPositionalEmbedding
  from pytorch_translate import char_encoder, char_source_model, hybrid_transformer_rnn, model_constants, rnn, transformer, utils, vocab_constants
  from pytorch_translate.common_layers import TransformerEncoderGivenEmbeddings, VariableTracker
  from pytorch_translate.data.dictionary import TAGS
label_desc: Use image node_id 2 for calling the CharCNNEncoder obj's underlying member method code with example usage: obj.prepare_for_onnx_export_() without return types